Kylie Anglin

Dr. Anglin is a methodologist who develops data science and natural language processing-based methods for understanding educational processes. Her most recent research develops automated methods for efficiently monitoring program implementation in impact evaluations, as well as methods for improving the causal validity and replicability of impact estimates. Her work has appeared in journals such as the Journal of Research on Educational Effectiveness, Prevention Science, AERA Open, and Evaluation Review. She received her Ph.D. from the University of Virginia, where she participated in the Institute for Education Sciences (IES) Pre-doctoral Training Program and received an NAEd/Spencer dissertation fellowship.